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增加“机器学习”和“数据分析”的块

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This commit is contained in:
13880560530
2024-11-29 08:53:29 +08:00
parent 28552b0a22
commit ead77c4b89
8 changed files with 141 additions and 28 deletions
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14
boards/default_src/python_mixpy/blocks/data.js
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@@ -1247,16 +1247,12 @@ export const pandas_drop_columns = {
this.appendValueInput('DATAFRAME')
.appendField('从数据集');
this.appendValueInput('COLUMNS')
.appendField('中删除列');
this.appendDummyInput()
.appendField('沿着axis')
.appendField(new Blockly.FieldDropdown([
['行', '0'],
['列', '1']
]), 'AXIS');
.appendField('中删除列')
.setCheck(String);
this.setInputsInline(true);
this.setOutput(true);
this.setTooltip('Drops columns from dataframe.');
}
this.setTooltip('从数据框中删除指定的列。用逗号分隔多个列名。');
},
};
export const numpy_ones = {

67
boards/default_src/python_mixpy/blocks/sklearn.js
View File

@@ -405,6 +405,49 @@ export const sklearn_GaussianNB = {
}
};
//sklearn 初始化PCA降维
export const sklearn_pca = {
init: function () {
this.appendDummyInput()
.appendField("sklearn 初始化 PCA 算法");
this.appendValueInput("model_name")
.setCheck(null)
.setAlign(Blockly.inputs.Align.RIGHT)
.appendField(Blockly.Msg.MODEL_NAME);
this.appendValueInput("n_components")
.setCheck(null)
.setAlign(Blockly.inputs.Align.RIGHT)
.appendField(Blockly.Msg.SKLEARN_PCA_N_COMPONENTS);
this.setInputsInline(false);
this.setPreviousStatement(true, null);
this.setNextStatement(true, null);
this.setColour(SKLEARN_HUE);
this.setTooltip("");
this.setHelpUrl("");
}
};
//sklearn PCA拟合并转换数据
export const sklearn_pca_fit_transform = {
init: function () {
this.appendDummyInput()
.appendField("sklearn PCA 降维");
this.appendValueInput("model_name")
.setCheck(null)
.setAlign(Blockly.inputs.Align.RIGHT)
.appendField(Blockly.Msg.MODEL_NAME);
this.appendValueInput("train_data")
.setCheck(null)
.setAlign(Blockly.inputs.Align.RIGHT)
.appendField(Blockly.Msg.EIGENVALUES);
this.setInputsInline(true);
this.setOutput(true, null);
this.setColour(SKLEARN_HUE);
this.setTooltip("");
this.setHelpUrl("");
}
};
//sklearn 初始化K-均值聚类
export const sklearn_KMeans = {
init: function () {
@@ -426,11 +469,29 @@ export const sklearn_KMeans = {
.setCheck(null)
.setAlign(Blockly.inputs.Align.RIGHT)
.appendField(Blockly.Msg.RANDOM_SEED);
this.appendValueInput("n_jobs")
this.setInputsInline(false);
this.setPreviousStatement(true, null);
this.setNextStatement(true, null);
this.setColour(SKLEARN_HUE);
this.setTooltip("");
this.setHelpUrl("");
}
};
//sklearn KMeans拟合数据
export const sklearn_KMeans_fit = {
init: function () {
this.appendDummyInput()
.appendField("sklearn K-均值聚类");
this.appendValueInput("model_name")
.setCheck(null)
.setAlign(Blockly.inputs.Align.RIGHT)
.appendField(Blockly.Msg.SKLEARN_THREADS);
this.setInputsInline(false);
.appendField(Blockly.Msg.MODEL_NAME);
this.appendValueInput("train_data")
.setCheck(null)
.setAlign(Blockly.inputs.Align.RIGHT)
.appendField(Blockly.Msg.EIGENVALUES);
this.setInputsInline(true);
this.setPreviousStatement(true, null);
this.setNextStatement(true, null);
this.setColour(SKLEARN_HUE);